Is $P(X|A,B)=frac{P(A|X)P(B|X)P(X)}{P(A)P(B)}$ when $A$ and $B$ are conditionally indepdent?
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I am trying to evaluate $P(X|A,B)$ given that $A$ and $B$ are conditionally independent given $X$. I know that this can be expressed as,
$$P(X|A,B)=frac{P(A,B,X)}{P(A,B)}$$
Using the conditional independence of $A$ and $B$ given $X$ this is,
$$frac{P(A|B,X)P(B,X)}{P(A)P(B)}=frac{P(A|X)P(B,X)}{P(A)P(B)}$$
Using the chain rule this is
$$frac{P(A|X)P(B|X)P(X)}{P(A)P(B)}$$
Is this correct? Does this hold with conditional independence of $A$ and $B$ given $X$, or does it also require independence alone of $A$ and $B$?
probability probability-theory bayes-theorem
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up vote
2
down vote
favorite
I am trying to evaluate $P(X|A,B)$ given that $A$ and $B$ are conditionally independent given $X$. I know that this can be expressed as,
$$P(X|A,B)=frac{P(A,B,X)}{P(A,B)}$$
Using the conditional independence of $A$ and $B$ given $X$ this is,
$$frac{P(A|B,X)P(B,X)}{P(A)P(B)}=frac{P(A|X)P(B,X)}{P(A)P(B)}$$
Using the chain rule this is
$$frac{P(A|X)P(B|X)P(X)}{P(A)P(B)}$$
Is this correct? Does this hold with conditional independence of $A$ and $B$ given $X$, or does it also require independence alone of $A$ and $B$?
probability probability-theory bayes-theorem
1
You split $P(A, B) = P(A)P(B)$ -- that is independence of $A, B$, not conditional independence.
– Mees de Vries
Nov 20 at 14:01
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up vote
2
down vote
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up vote
2
down vote
favorite
I am trying to evaluate $P(X|A,B)$ given that $A$ and $B$ are conditionally independent given $X$. I know that this can be expressed as,
$$P(X|A,B)=frac{P(A,B,X)}{P(A,B)}$$
Using the conditional independence of $A$ and $B$ given $X$ this is,
$$frac{P(A|B,X)P(B,X)}{P(A)P(B)}=frac{P(A|X)P(B,X)}{P(A)P(B)}$$
Using the chain rule this is
$$frac{P(A|X)P(B|X)P(X)}{P(A)P(B)}$$
Is this correct? Does this hold with conditional independence of $A$ and $B$ given $X$, or does it also require independence alone of $A$ and $B$?
probability probability-theory bayes-theorem
I am trying to evaluate $P(X|A,B)$ given that $A$ and $B$ are conditionally independent given $X$. I know that this can be expressed as,
$$P(X|A,B)=frac{P(A,B,X)}{P(A,B)}$$
Using the conditional independence of $A$ and $B$ given $X$ this is,
$$frac{P(A|B,X)P(B,X)}{P(A)P(B)}=frac{P(A|X)P(B,X)}{P(A)P(B)}$$
Using the chain rule this is
$$frac{P(A|X)P(B|X)P(X)}{P(A)P(B)}$$
Is this correct? Does this hold with conditional independence of $A$ and $B$ given $X$, or does it also require independence alone of $A$ and $B$?
probability probability-theory bayes-theorem
probability probability-theory bayes-theorem
edited Nov 20 at 13:58
asked Nov 19 at 23:59
user617643
226
226
1
You split $P(A, B) = P(A)P(B)$ -- that is independence of $A, B$, not conditional independence.
– Mees de Vries
Nov 20 at 14:01
add a comment |
1
You split $P(A, B) = P(A)P(B)$ -- that is independence of $A, B$, not conditional independence.
– Mees de Vries
Nov 20 at 14:01
1
1
You split $P(A, B) = P(A)P(B)$ -- that is independence of $A, B$, not conditional independence.
– Mees de Vries
Nov 20 at 14:01
You split $P(A, B) = P(A)P(B)$ -- that is independence of $A, B$, not conditional independence.
– Mees de Vries
Nov 20 at 14:01
add a comment |
2 Answers
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You could save some steps using Bayes' formula:
$$
P(X mid A, B) = frac{P(A, B mid X)P(X)}{P(A, B)}
$$
Using the conditional independence, this is
$$
frac{P(A mid X) P(B mid X) P(X)}{P(A, B)}
$$
But as has been pointed out, you cannot factor the denominator without assuming independence of $A$ and $B$
Thanks! I would upvote your answer but due to my low reputation the system does not permit me.
– user617643
Nov 20 at 14:29
add a comment |
up vote
0
down vote
Almost correct:
$$P(X|A,B) = frac{P(A|X)P(B|X)P(X)}{P(A,B)}$$
You know that A and B are conditionally independent given X but not that A and B are independent (that cannot be assumed).
Thanks! I would upvote your answer but due to my low reputation the system does not permit me.
– user617643
Nov 20 at 14:29
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
accepted
You could save some steps using Bayes' formula:
$$
P(X mid A, B) = frac{P(A, B mid X)P(X)}{P(A, B)}
$$
Using the conditional independence, this is
$$
frac{P(A mid X) P(B mid X) P(X)}{P(A, B)}
$$
But as has been pointed out, you cannot factor the denominator without assuming independence of $A$ and $B$
Thanks! I would upvote your answer but due to my low reputation the system does not permit me.
– user617643
Nov 20 at 14:29
add a comment |
up vote
0
down vote
accepted
You could save some steps using Bayes' formula:
$$
P(X mid A, B) = frac{P(A, B mid X)P(X)}{P(A, B)}
$$
Using the conditional independence, this is
$$
frac{P(A mid X) P(B mid X) P(X)}{P(A, B)}
$$
But as has been pointed out, you cannot factor the denominator without assuming independence of $A$ and $B$
Thanks! I would upvote your answer but due to my low reputation the system does not permit me.
– user617643
Nov 20 at 14:29
add a comment |
up vote
0
down vote
accepted
up vote
0
down vote
accepted
You could save some steps using Bayes' formula:
$$
P(X mid A, B) = frac{P(A, B mid X)P(X)}{P(A, B)}
$$
Using the conditional independence, this is
$$
frac{P(A mid X) P(B mid X) P(X)}{P(A, B)}
$$
But as has been pointed out, you cannot factor the denominator without assuming independence of $A$ and $B$
You could save some steps using Bayes' formula:
$$
P(X mid A, B) = frac{P(A, B mid X)P(X)}{P(A, B)}
$$
Using the conditional independence, this is
$$
frac{P(A mid X) P(B mid X) P(X)}{P(A, B)}
$$
But as has been pointed out, you cannot factor the denominator without assuming independence of $A$ and $B$
answered Nov 20 at 14:26
Slug Pue
2,15111020
2,15111020
Thanks! I would upvote your answer but due to my low reputation the system does not permit me.
– user617643
Nov 20 at 14:29
add a comment |
Thanks! I would upvote your answer but due to my low reputation the system does not permit me.
– user617643
Nov 20 at 14:29
Thanks! I would upvote your answer but due to my low reputation the system does not permit me.
– user617643
Nov 20 at 14:29
Thanks! I would upvote your answer but due to my low reputation the system does not permit me.
– user617643
Nov 20 at 14:29
add a comment |
up vote
0
down vote
Almost correct:
$$P(X|A,B) = frac{P(A|X)P(B|X)P(X)}{P(A,B)}$$
You know that A and B are conditionally independent given X but not that A and B are independent (that cannot be assumed).
Thanks! I would upvote your answer but due to my low reputation the system does not permit me.
– user617643
Nov 20 at 14:29
add a comment |
up vote
0
down vote
Almost correct:
$$P(X|A,B) = frac{P(A|X)P(B|X)P(X)}{P(A,B)}$$
You know that A and B are conditionally independent given X but not that A and B are independent (that cannot be assumed).
Thanks! I would upvote your answer but due to my low reputation the system does not permit me.
– user617643
Nov 20 at 14:29
add a comment |
up vote
0
down vote
up vote
0
down vote
Almost correct:
$$P(X|A,B) = frac{P(A|X)P(B|X)P(X)}{P(A,B)}$$
You know that A and B are conditionally independent given X but not that A and B are independent (that cannot be assumed).
Almost correct:
$$P(X|A,B) = frac{P(A|X)P(B|X)P(X)}{P(A,B)}$$
You know that A and B are conditionally independent given X but not that A and B are independent (that cannot be assumed).
answered Nov 20 at 14:15
DavidPM
16618
16618
Thanks! I would upvote your answer but due to my low reputation the system does not permit me.
– user617643
Nov 20 at 14:29
add a comment |
Thanks! I would upvote your answer but due to my low reputation the system does not permit me.
– user617643
Nov 20 at 14:29
Thanks! I would upvote your answer but due to my low reputation the system does not permit me.
– user617643
Nov 20 at 14:29
Thanks! I would upvote your answer but due to my low reputation the system does not permit me.
– user617643
Nov 20 at 14:29
add a comment |
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1
You split $P(A, B) = P(A)P(B)$ -- that is independence of $A, B$, not conditional independence.
– Mees de Vries
Nov 20 at 14:01